osprai/trunk/ba_class.py

"""
ba_class
--------

Biosensor Array class for storing SPRI data.
This contains an array of SPR sensorgrams with their
associated models and parameters.
This can also contain the microarray geometery.

.. moduleauthor:: Christopher Lausted, 
                  Institute for Systems Biology, 
                  Yuhang Wan,
                  OSPRAI developers.   
                  
Examples::

  >>> ba1 = BiosensorArray(800,1500)     ## Allocate object with 800 spots of 1500 time points.
  >>> ba1.roi[799].time[1499] = 7502.1   ## Set time in seconds.
  >>> ba1.roi[799].value[1499] = 0.50    ## Set SPR reflectance signal. 
  >>> ba1.roi[799].name = "anti-IgG"     ## Set name of microarray feature.
"""
__version__ = "110204"


## Import libraries.
import numpy as np
#import matplotlib.pyplot as plt
from datetime import date


class BiosensorArray(object):
    """
    The Biosensor Array class holds all ROIs (spots)
    from an SPRI microarray run.
    
    ================ =============== =======================================
    Property         Type            Description
    ---------------- --------------- ---------------------------------------
    roi              list of object  List of RegOfInterest objects.
    rois             integer         Size of roi (Number of ROIs).
    dpoints          integer         Number of datapoints in each ROI.
    primarydatafiles list of string  List of file names.
    comments         list of string  List of comments regarding experiments.
    ================ =============== =======================================
    """
    
    def __init__(self, roi_size, datapoint_size):
        """This object is dimensioned upon initialization.""" ## Might improve speed.
        ## Use a list comprehension to dimension list of classes.
        self.roi = [RegOfInterest(i,datapoint_size) for i in range(roi_size)] 
        ## Remember the dimensions for quick bounds-checking later.
        self.rois = roi_size
        self.dpoints = datapoint_size
        ## Use these to keep track of laboratory notes.
        self.primarydatafiles = [""]  ## Like "spritdata.txt"
        self.comments = [""]          ## Like "Antibody data from 1 Jan 2010"
        return
        
    def xy2uid(self, gx, gy, x, y):
        """Given roi coordinates, find corresponding uid (index)."""
        coor1 = (gx, gy, x, y)
        for ob in self.roi:
            coor2 = (ob.gridx, ob.gridy, ob.spotx, ob.spoty)
            if (coor1==coor2): return ob.uid  ## Success.
        return -1  ## Failure.
        
    def set_plot_all(self):
        """Choose to plot every sensorgram."""
        for ob in self.roi: ob.plottable = True
        return
        
    def set_plot_list(self, ilist):
        """Choose a list of sensorgrams to plot"""
        for ob in self.roi: ob.plottable = False
        for i in ilist: self.roi[i].plottable = True
        return
        
    ## A pyplot feature for testing purposes.
    def plot(self):
        """Show plot of the selected sensorgrams."""
        plt.clf()
        plt.title('SPR Data plotted %s' % date.today().isoformat())
        plt.xlabel('Time (s)')
        plt.ylabel('SPR Response')
        plt.grid(True)
        ## Plot traces.
        for ob in self.roi:
            if (ob.plottable==True):
                mylabel = "%i:%s" % (ob.index,ob.name)
                plt.plot(ob.time, ob.value, label=mylabel)
        plt.legend(loc='best')
        plt.show()
        return
        
    """End of BiosensorArray class definition."""


class RegOfInterest(object):
    """
    This Region Of Interest class can hold one SPR sensorgram.
    
    =========== =============== =============================================
    Property    Type            Description
    ----------- --------------- ---------------------------------------------
    uid         integer         Unique ID integer. Never changes.
    index       integer         Changes if ba size changes (add/remove rois).
    time        nparray         Usually seconds.
    value       nparray         Arbitrary units.
    dpoints     integer         Can use for bounds checking.
    name        string          Name of ROI.
    desc        string          Description of ROI
    
    gridx       integer         Can be Block number from GAL file.  
    gridy       integer         Unused?
    spotx       integer         ROI column number.
    spoty       integer         ROI row number.
    bgroi       list of integer One or more background ROIs.
    calibM      float           Slope used for calibration
    calibB      float           Intercept used for calibration.
    plottable   boolean         Whether to plot
    
    injconc     list of float   One or more analyte concentrations.
    injstart    list of float   One or more injection start times.
    injstop     list of float   One or more injection start times.
    injrind     list of float   One or more expected refractive index jumps.
    
    flow        float           Flowrate of injection.
    model       ref to funct    Model describing this ROI. 
    params      dict of dict    Parameters for this model. 
    =========== =============== =============================================
    """
    
    def __init__(self, i, datapoint_size):
        """
        Each ROI in a list needs a unique ID number which will be i+1.
        The time and value arrays must be allocated using datapoint_size.
        """
        self.uid = i+1            ## Unique ID integer. Never changes.
        self.index = i            ## Changes if ba size changes (add/remove rois).
        self.time = np.zeros(datapoint_size, dtype=float)  ## Usually seconds.
        self.value = np.zeros(datapoint_size, dtype=float) ## Arbitrary units.
        self.dpoints = datapoint_size  ## Can use for bounds checking.
        ## Useful optional information. Usually from GAL or Key files.
        self.name = "Spot%i" % (i+1)
        self.desc = "Description"
        self.gridx = 0            ## Can be Block number from GAL file.  
        self.gridy = 0            ## Unused?
        self.spotx = 0            ## ROI column number.
        self.spoty = 0            ## ROI row number.
        self.bgroi = [0]          ## One or more background ROIs.
        self.calibM = 1           ## Slope used for calibration
        self.calibB = 0           ## Intercept used for calibration.
        self.plottable = True     ## Whether to plot
        ## Optional injection information. Usually from Clamp or ICM Method files.
        self.injconc = [0.0]     ## One or more analyte concentrations.
        self.injstart = [0.0]    ## One or more injection start times.
        self.injstop = [0.0]     ## One or more injection start times.
        self.injrind = [0.0]     ## One or more expected refractive index jumps.
        self.flow = 0            ## Flowrate of injection.
        ## Curve fitting information.  Model and model parameters.
        ## Example model is reference to function like data=simple1to1(times,params)
        ## Example params = {'Rmax': {'value':1, 'min':0, 'max':10, 'fixed':'float'} } 
        self.model = None    ## Model describing this roi. Reference to a function.
        self.params = []     ## Parameters for this model. A dictionary of dictionaries.
        
    def time2dp(self, t):
        """Find datapoint closest to given time."""
        pos2 = self.time.searchsorted(t)    ## Time point just after t.
        pos2 = min(pos2, len(self.time)-1)  ## Avoid indexing error.
        pos1 = max(pos2-1,0)                ## Time point just before t.
        t2 = abs(self.time[pos2] - t)
        t1 = abs(self.time[pos1] - t)
        ## Decide if time point just before or just after is closer.
        if (t2<t1): 
            return pos2
        else: 
            return pos1
            
    def time2val(self, t1, t2):
        """Return list of SPR values between t1 and t2"""
        dp1, dp2 = self.time2dp(t1), self.time2dp(t2)
        return [self.value[i] for i in range(dp1, dp2)]
    
    """End of RegOfInterest definition."""

'''
## Here are a few lines to test this class.
if __name__ == '__main__':
    print "Starting demo..."
    print "Test plotting..."
    x = BiosensorArray(10,10)
    x.roi[0].time = np.arange(10)
    x.roi[0].value = np.arange(10)**2
    x.roi[1].time = np.arange(10)
    x.roi[1].value = np.arange(10)**1.5
    x.roi[9].time = np.arange(10)
    x.roi[9].value = np.arange(10)**1
    #x.set_plot_all()
    x.set_plot_list([0,1,9])
    x.plot()
    print "Test xy2uid... 9 =",
    x.roi[9].gridx = 2
    print x.xy2uid(2,0,0,0)
    print "Test time2dp... 5.6 =>",
    print x.roi[9].time2dp(5.6)
    print "Demo finished."
'''
    
    
################################# End of module #################################
Revision:	48
Committed:	Fri Feb 4 19:09:24 2011 UTC (8 years ago) by clausted
File size:	8821 byte(s)
Log Message:	Minor formatting.
Line	File contents
1	"""
2	ba_class
3	--------
4
5	Biosensor Array class for storing SPRI data.
6	This contains an array of SPR sensorgrams with their
7	associated models and parameters.
8	This can also contain the microarray geometery.
9
10	.. moduleauthor:: Christopher Lausted,
11	Institute for Systems Biology,
12	Yuhang Wan,
13	OSPRAI developers.
14
15	Examples::
16
17	>>> ba1 = BiosensorArray(800,1500) ## Allocate object with 800 spots of 1500 time points.
18	>>> ba1.roi[799].time[1499] = 7502.1 ## Set time in seconds.
19	>>> ba1.roi[799].value[1499] = 0.50 ## Set SPR reflectance signal.
20	>>> ba1.roi[799].name = "anti-IgG" ## Set name of microarray feature.
21	"""
22	__version__ = "110204"
23
24
25	## Import libraries.
26	import numpy as np
27	#import matplotlib.pyplot as plt
28	from datetime import date
29
30
31	class BiosensorArray(object):
32	"""
33	The Biosensor Array class holds all ROIs (spots)
34	from an SPRI microarray run.
35
36	================ =============== =======================================
37	Property Type Description
38	---------------- --------------- ---------------------------------------
39	roi list of object List of RegOfInterest objects.
40	rois integer Size of roi (Number of ROIs).
41	dpoints integer Number of datapoints in each ROI.
42	primarydatafiles list of string List of file names.
43	comments list of string List of comments regarding experiments.
44	================ =============== =======================================
45	"""
46
47	def __init__(self, roi_size, datapoint_size):
48	"""This object is dimensioned upon initialization.""" ## Might improve speed.
49	## Use a list comprehension to dimension list of classes.
50	self.roi = [RegOfInterest(i,datapoint_size) for i in range(roi_size)]
51	## Remember the dimensions for quick bounds-checking later.
52	self.rois = roi_size
53	self.dpoints = datapoint_size
54	## Use these to keep track of laboratory notes.
55	self.primarydatafiles = [""] ## Like "spritdata.txt"
56	self.comments = [""] ## Like "Antibody data from 1 Jan 2010"
57	return
58
59	def xy2uid(self, gx, gy, x, y):
60	"""Given roi coordinates, find corresponding uid (index)."""
61	coor1 = (gx, gy, x, y)
62	for ob in self.roi:
63	coor2 = (ob.gridx, ob.gridy, ob.spotx, ob.spoty)
64	if (coor1==coor2): return ob.uid ## Success.
65	return -1 ## Failure.
66
67	def set_plot_all(self):
68	"""Choose to plot every sensorgram."""
69	for ob in self.roi: ob.plottable = True
70	return
71
72	def set_plot_list(self, ilist):
73	"""Choose a list of sensorgrams to plot"""
74	for ob in self.roi: ob.plottable = False
75	for i in ilist: self.roi[i].plottable = True
76	return
77
78	## A pyplot feature for testing purposes.
79	def plot(self):
80	"""Show plot of the selected sensorgrams."""
81	plt.clf()
82	plt.title('SPR Data plotted %s' % date.today().isoformat())
83	plt.xlabel('Time (s)')
84	plt.ylabel('SPR Response')
85	plt.grid(True)
86	## Plot traces.
87	for ob in self.roi:
88	if (ob.plottable==True):
89	mylabel = "%i:%s" % (ob.index,ob.name)
90	plt.plot(ob.time, ob.value, label=mylabel)
91	plt.legend(loc='best')
92	plt.show()
93	return
94
95	"""End of BiosensorArray class definition."""
96
97
98	class RegOfInterest(object):
99	"""
100	This Region Of Interest class can hold one SPR sensorgram.
101
102	=========== =============== =============================================
103	Property Type Description
104	----------- --------------- ---------------------------------------------
105	uid integer Unique ID integer. Never changes.
106	index integer Changes if ba size changes (add/remove rois).
107	time nparray Usually seconds.
108	value nparray Arbitrary units.
109	dpoints integer Can use for bounds checking.
110	name string Name of ROI.
111	desc string Description of ROI
112
113	gridx integer Can be Block number from GAL file.
114	gridy integer Unused?
115	spotx integer ROI column number.
116	spoty integer ROI row number.
117	bgroi list of integer One or more background ROIs.
118	calibM float Slope used for calibration
119	calibB float Intercept used for calibration.
120	plottable boolean Whether to plot
121
122	injconc list of float One or more analyte concentrations.
123	injstart list of float One or more injection start times.
124	injstop list of float One or more injection start times.
125	injrind list of float One or more expected refractive index jumps.
126
127	flow float Flowrate of injection.
128	model ref to funct Model describing this ROI.
129	params dict of dict Parameters for this model.
130	=========== =============== =============================================
131	"""
132
133	def __init__(self, i, datapoint_size):
134	"""
135	Each ROI in a list needs a unique ID number which will be i+1.
136	The time and value arrays must be allocated using datapoint_size.
137	"""
138	self.uid = i+1 ## Unique ID integer. Never changes.
139	self.index = i ## Changes if ba size changes (add/remove rois).
140	self.time = np.zeros(datapoint_size, dtype=float) ## Usually seconds.
141	self.value = np.zeros(datapoint_size, dtype=float) ## Arbitrary units.
142	self.dpoints = datapoint_size ## Can use for bounds checking.
143	## Useful optional information. Usually from GAL or Key files.
144	self.name = "Spot%i" % (i+1)
145	self.desc = "Description"
146	self.gridx = 0 ## Can be Block number from GAL file.
147	self.gridy = 0 ## Unused?
148	self.spotx = 0 ## ROI column number.
149	self.spoty = 0 ## ROI row number.
150	self.bgroi = [0] ## One or more background ROIs.
151	self.calibM = 1 ## Slope used for calibration
152	self.calibB = 0 ## Intercept used for calibration.
153	self.plottable = True ## Whether to plot
154	## Optional injection information. Usually from Clamp or ICM Method files.
155	self.injconc = [0.0] ## One or more analyte concentrations.
156	self.injstart = [0.0] ## One or more injection start times.
157	self.injstop = [0.0] ## One or more injection start times.
158	self.injrind = [0.0] ## One or more expected refractive index jumps.
159	self.flow = 0 ## Flowrate of injection.
160	## Curve fitting information. Model and model parameters.
161	## Example model is reference to function like data=simple1to1(times,params)
162	## Example params = {'Rmax': {'value':1, 'min':0, 'max':10, 'fixed':'float'} }
163	self.model = None ## Model describing this roi. Reference to a function.
164	self.params = [] ## Parameters for this model. A dictionary of dictionaries.
165
166	def time2dp(self, t):
167	"""Find datapoint closest to given time."""
168	pos2 = self.time.searchsorted(t) ## Time point just after t.
169	pos2 = min(pos2, len(self.time)-1) ## Avoid indexing error.
170	pos1 = max(pos2-1,0) ## Time point just before t.
171	t2 = abs(self.time[pos2] - t)
172	t1 = abs(self.time[pos1] - t)
173	## Decide if time point just before or just after is closer.
174	if (t2<t1):
175	return pos2
176	else:
177	return pos1
178
179	def time2val(self, t1, t2):
180	"""Return list of SPR values between t1 and t2"""
181	dp1, dp2 = self.time2dp(t1), self.time2dp(t2)
182	return [self.value[i] for i in range(dp1, dp2)]
183
184	"""End of RegOfInterest definition."""
185
186	'''
187	## Here are a few lines to test this class.
188	if __name__ == '__main__':
189	print "Starting demo..."
190	print "Test plotting..."
191	x = BiosensorArray(10,10)
192	x.roi[0].time = np.arange(10)
193	x.roi[0].value = np.arange(10)**2
194	x.roi[1].time = np.arange(10)
195	x.roi[1].value = np.arange(10)**1.5
196	x.roi[9].time = np.arange(10)
197	x.roi[9].value = np.arange(10)**1
198	#x.set_plot_all()
199	x.set_plot_list([0,1,9])
200	x.plot()
201	print "Test xy2uid... 9 =",
202	x.roi[9].gridx = 2
203	print x.xy2uid(2,0,0,0)
204	print "Test time2dp... 5.6 =>",
205	print x.roi[9].time2dp(5.6)
206	print "Demo finished."
207	'''
208
209
210	################################# End of module #################################